Gotowe bibliografie tematyczne / Data Visualisation

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Gotowa bibliografia na temat „Data Visualisation”

Autor: Grafiati

Data publikacji: 4 czerwca 2021

Data aktualizacji: 9 czerwca 2025

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Artykuły w czasopismach na temat "Data Visualisation"

Garrote, Antonio, and María N. Moreno García. "LinkedVis an Information Visualisation Toolkit for RDF Data." International Journal on Semantic Web and Information Systems 9, no. 4 (October 2013): 1–16. http://dx.doi.org/10.4018/ijswis.2013100101.

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LinkedVis implements a JavaScript and SVG data visualisation toolkit that can be used to generate a wide range of interactive information visualisations from RDF graphs using a grammar of graphics style syntax extended with operations for structural transformation of the RDF data graph. Additionally, LinkedVis visualisations make it possible to embed meta-data about the visualisation and the way different graphic components from the visualisation are related to the original RDF data. Insertion of meta-data transforms the visualisation into a self-describing piece of information that can be processed by an automatic agent to perform different tasks, like extracting data associated to a visual component, following the associated linked URIs or translate the visualisation to an entirely different underlying graphics system other than SVG.

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Meier, Sebastian, and Katrin Glinka. "The Individual in the Data — the Aspect of Personal Relevance in Designing Casual Data Visualisations." i-com 16, no. 3 (December 20, 2017): 247–65. http://dx.doi.org/10.1515/icom-2017-0025.

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AbstractOver the last two decades, data visualisation has diffused into the broader realm of mass communication. Before this shift, tools and displays of data-driven geographic- and information visualisation were mostly used in expert contexts. By now, they are also used in casual contexts, for example on newspaper websites, government data portals and many other public outlets. This diversification of the audience poses new challenges within the visualisation community. In this paper we propose personal relevance as one factor to be taken into account when designing casual data visualisations, which are meant for the communication with non-experts. We develop a conceptual model and present a related set of design techniques for interactive web-based visualisations that are aimed at activating personal relevance. We discuss our proposed techniques by applying them to a use case on the visualisation of air pollution in London (UK).

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Nash, Kathryn, Verity Trott, and William Allen. "The politics of data visualisation and policy making." Convergence: The International Journal of Research into New Media Technologies 28, no. 1 (February 2022): 3–12. http://dx.doi.org/10.1177/13548565221079156.

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Data visualisation has become ubiquitous in everyday life, from seeing images in news media to tracking individual health indicators. While the effects of data visualisation on society and people have been explored within a range of literature, there has been far less attention paid to the interconnectedness of data visualisation and policy making. In this special issue, we explore how data visualisation matters for policy priorities, processes and outcomes; how it reflects the demands and constraints posed by specific policy problems; and finally, what data visualisations reveal about broader political, social, and cultural shifts and the implications for policy.

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Allen, William L. "Visual brokerage: Communicating data and research through visualisation." Public Understanding of Science 27, no. 8 (February 5, 2018): 906–22. http://dx.doi.org/10.1177/0963662518756853.

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Researchers increasingly use visualisation to make sense of their data and communicate findings more widely. But these are not necessarily straightforward processes. Theories of knowledge brokerage show how sociopolitical contexts and intermediary organisations that translate research for public audiences shape how users engage with evidence. Applying these ideas to data visualisation, I argue that several kinds of brokers (such as data collectors, designers and intermediaries) link researchers and audiences, contributing to the ways that people engage with visualisations. To do this, I draw on qualitative focus groups that elicited non-academic viewers’ reactions to visualisations of data about UK migration. The results reveal two important features of engagement: perceptions of brokers’ credibility and feelings of surprise arising from visualisations’ content and design. I conclude by arguing that researchers, knowledge brokers and the public produce – as well as operate within – a complex visualisation space characterised by mutual, bi-directional connections.

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Hill, Rosemary Lucy. "The political potential of numbers: data visualisation in the abortion debate." Kvinder, Køn & Forskning, no. 1 (September 5, 2017): 83–96. http://dx.doi.org/10.7146/kkf.v26i1.109789.

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Data visualisation has been argued to have the power to ‘change the world’, implicitly for the better, but when it comes to abortion, both sides make moral claims to ‘good’. Visualisation conventions of clean lines and shapes simplify data, lending them a rhetoric of neutrality, as if the data is the whole story. It is imperative, therefore, to examine how data visualisations are used to shape women’s lives. This article draws on the findings of the Persuasive Data project . Google Image Scraper was used to locate abortion-related visualisations circulating online. The images, their web locations, and data use were social semiotically analysed to understand their visual rhetoric and political use. Anti-abortion groups are more likely to use data visualisation than pro-choice groups, thereby simplifying the issue and mobilising the rhetoric of neutrality. I argue that data visualisations are being used as a hindrance to women’s access to abortion, and that the critique of such visualisations needs to come from feminists. This article extends discussions of how data is often reified as objective, by showing how the rhetoric of objectivity within data visualisation conventions is harnessed to do work in the world that is potentially very damaging to women’s rights.

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Kirsten, Marnell, Marina Joubert, Ionica Smeets, and Winnifred Wijnker. "Off the charts: A comparative analysis of data visualisations in online science news from South Africa and the USA." PLOS ONE 20, no. 2 (February 21, 2025): e0316194. https://doi.org/10.1371/journal.pone.0316194.

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Terms like ‘big data’, ‘data science’, and ‘data visualisation’ have become buzzwords in recent years and are increasingly intertwined with journalism. Data visualisation may further blur the lines between science communication and graphic design. Our study is situated in these overlaps to compare the design of data visualisations in science news stories across four online news media platforms in South Africa and the United States. Our study contributes to an understanding of how well-considered data visualisations are tools for effective storytelling, and offers practical recommendations for using data visualisation in science communication efforts.

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ROHIT, SINGH, Kumar Pandya Nitin, Kruti Sutariya Dr., and Amit Barve Dr. "AlgoPedia." International Journal of Innovative Science and Research Technology 8, no. 3 (March 31, 2023): 1466–85. https://doi.org/10.5281/zenodo.7789144.

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Data visualisation entails presenting information in a graphical or pictorial format that is easy to understand. It aids in the explanation of facts and the formulation of action plans. It will be useful in any field of study that requires novel approaches to presenting large amounts of complex information. The introduction of computer graphics shaped modern visualisation. This paper provides an overview of data visualisation. Data visualisation, information visualisation, scientific visualisation, and big data are all keywords. Information visualisation and scientific visualisation are other terms for data visualisation. Humans have always used visualisations to make messages or information last longer. What cannot be touched, smelled, or tasted can be visually represented.

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Donohoe, David, and Eamon Costello. "Data Visualisation Literacy in Higher Education: An Exploratory Study of Understanding of a Learning Dashboard Tool." International Journal of Emerging Technologies in Learning (iJET) 15, no. 17 (September 11, 2020): 115. http://dx.doi.org/10.3991/ijet.v15i17.15041.

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The visualisation of data has become ubiquitous. Visualisations are used to represent data in a way that is easy to understand and useful in our lives. Each data visualisation needs to be suitable to extract the correct information to complete a task and make an informed decision while minimising the impact of biases. To achieve this, the ability to create and read visualisations has become as important as the ability to read and write. Therefore, the Information Visualisation community is applying more attention to literacy and decision making in data vis-ualisations. Until recently, researchers lacked valid and reliable test in-struments to measure the literacy of users or the taxonomy to detect biased judgement in data visualisations. A literature review showed there is relatively little research on data visualisations for different user data literacy levels in authentic settings and a lack of studies that pro-vide evidence for the presence of cognitive biases in data visualisa-tions. This exploratory research study was undertaken to develop a method to assess perceived usefulness and confidence in reporting dashboards within higher education by adapting existing research in-struments. A survey was designed to test perceived usefulness, per-ceived skill and 24 multiple-choice test items covering six data visuali-sations based on eight tasks. The study was sent to 157 potential par-ticipants, with a response rate of 20.38%. The results showed data vis-ualisations are useful, but the purpose of some data visualisations is not always understood. Also, we showed there is a consensus that re-spondents perceive their data visualisation literacy is higher than they believe their peers to be. However, the higher their overconfidence, the lower their actual data visualisation literacy score. Finally, we discuss the benefits, limitations and possible future research areas.

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Sibolla, B. H., T. Van Zyl, and S. Coetzee. "TOWARDS THE DEVELOPMENT OF A TAXONOMY FOR VISUALISATION OF STREAMED GEOSPATIAL DATA." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-2 (June 2, 2016): 129–36. http://dx.doi.org/10.5194/isprsannals-iii-2-129-2016.

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Geospatial data has very specific characteristics that need to be carefully captured in its visualisation, in order for the user and the viewer to gain knowledge from it. The science of visualisation has gained much traction over the last decade as a response to various visualisation challenges. During the development of an open source based, dynamic two-dimensional visualisation library, that caters for geospatial streaming data, it was found necessary to conduct a review of existing geospatial visualisation taxonomies. The review was done in order to inform the design phase of the library development, such that either an existing taxonomy can be adopted or extended to fit the needs at hand. The major challenge in this case is to develop dynamic two dimensional visualisations that enable human interaction in order to assist the user to understand the data streams that are continuously being updated. This paper reviews the existing geospatial data visualisation taxonomies that have been developed over the years. Based on the review, an adopted taxonomy for visualisation of geospatial streaming data is presented. Example applications of this taxonomy are also provided. The adopted taxonomy will then be used to develop the information model for the visualisation library in a further study.

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Rozprawy doktorskie na temat "Data Visualisation"

Long, Elena. "Election data visualisation." Thesis, University of Plymouth, 2013. http://hdl.handle.net/10026.1/1589.

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Visualisations of election data produced by the mass media, other organisations and even individuals are becoming increasingly available across a wide variety of platforms and in many different forms. As more data become available digitally and as improvements to computer hardware and software are made, these visualisations have become more ambitious in scope and more user-friendly. Research has shown that visualising data is an extremely powerful method of communicating information to specialists and non-specialists alike. This amounts to a democratisation of access to political and electoral data. To some extent political science lags behind the progress that has been made in the field of data visualisation. Much of the academic output remains committed to the paper format and much of the data presentation is in the form of simple text and tables. In the digital and information age there is a danger that political science will fall behind. This thesis reports on a number of case studies where efforts were made to visualise election data in order to clarify its structure and to present its meaning. The first case study demonstrates the value of data visualisation to the research process itself, facilitating the understanding of effects produced by different ways of estimating missing data. A second study sought to use visualisation to explain complex aspects of voting systems to the wider public. Three further case studies demonstrate the value of collaboration between political scientists and others possessing a range of skills embracing data management, software engineering, broadcasting and graphic design. These studies also demonstrate some of the problems that are encountered when trying to distil complex data into a form that can be easily viewed and interpreted by non-expert users. More importantly, these studies suggest that when the skills balance is correct then visualisation is both viable and necessary for communicating information on elections.

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Eyre-Todd, Richard A. "Safe data structure visualisation." Thesis, University of Edinburgh, 1993. http://hdl.handle.net/1842/14819.

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A simple three layer scheme is presented which broadly categorises the types of support that a computing system might provide for program monitoring and debugging, namely hardware, language and external software support. Considered as a whole , the scheme forms a model for an integrated debugging-oriented system architecture. This thesis describes work which spans the upper levels of this architecture. A programming language may support debugging by preventing or detecting the use of objects that have no value. Techniques to help with this task such as formal verification, static analysis, required initialisation and default initialisation are considered. Strategies for tracking variable status at run-time are discussed. Novel methods are presented for adding run-time pointer variable checking to a language that does not normally support this facility. Language constructs that allow the selective control of run-time unassigned variable checking for scalar and composite objects are also described. Debugging at a higher level often involves the extensive examination of a program's data structures. The problem of visualising a particular kind of data structure, the hierarchic graph, is discussed using the previously described language level techniques to ensure data validity. The elementary theory of a class of two-level graphs is presented, together with several algorithms to perform a clustering technique that can improve graph layout and aid understanding.

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Garda-Osorio, Cesar. "Data mining and visualisation." Thesis, University of the West of Scotland, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.742763.

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Fei, Bennie Kar Leung. "Data visualisation in digital forensics." Pretoria : [s.n.], 2007. http://upetd.up.ac.za/thesis/available/etd-03072007-153241.

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Basalaj, Wojciech. "Proximity visualisation of abstract data." Thesis, University of Cambridge, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.620911.

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Anderson, Jonathan. "Visualisation of data from IoT systems : A case study of a prototyping tool for data visualisations." Thesis, Linköpings universitet, Programvara och system, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-138723.

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The client in this study, Attentec, has seen an increase in the demand for services connected to Internet of things systems. This study is therefore examining if there is a tool that can be a used to build fast prototype visualisations of data from IoT systems to use as a tool in their daily work. The study started with an initial phase with two parts. The first part was to get better knowledge of Attentec and derive requirements for the tool and the second part was a comparison of prototyping tools for aiding in development of data visualisations. Apache Zeppelin was chosen as the most versatile and suitable tool matching the criteria defined together with Attentec. Following the initial phase a pre-study containing interviews to collect empirical data on how visualisations and IoT projects had been implemented previously at Attentec were performed. This lead to the conclusion that geospatial data and NoSQL databases were common for IoT projects. A technical investigation was conducted on Apache Zeppelin to answer if there were any limits in using the tool for characteristics common in IoT system. This investigation lead to the conclusion that there was no support for plotting data on a map. The first implementation phase implemented support for geospatial data by adding a visualisation plug-in that plotted data on a map. The implementation phase was followed by an evaluation phase in which 5 participants performed tasks with Apache Zeppelin to evaluate the perceived usability of the tool. The evaluation was performed using a System Usability Scale and a Summed Usability Metric as well as interviews with the participants to find where improvements could be made. From the evaluation three main problems were discovered, the import and mapping of data, more feature on the map visualisation plug-in and the creation of database queries. The first two were chosen for the second iteration where a script for generating the code to import data was developed as well as improvements to the geospatial visualisation plug-in. A second evaluation was performed after the changes were made using similar tasks as in the first to see if the usability was improved between the two evaluations. The results of the Summed Usability Metric improved on all tasks and the System Usability Scale showed no significant change. In the interviews with the participants they all responded that the perceived usability had improved between the two evaluations suggesting some improvement.

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Gel, Moreno Bernat. "Dissemination and visualisation of biological data." Doctoral thesis, Universitat Politècnica de Catalunya, 2014. http://hdl.handle.net/10803/283143.

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With the recent advent of various waves of technological advances, the amount of biological data being generated has exploded. As a consequence of this data deluge, new challenges have emerged in the field of biological data management. In order to maximize the knowledge extracted from the huge amount of biological data produced it is of great importance for the research community that data dissemination and visualisation challenges are tackled. Opening and sharing our data and working collaboratively will benefit the scientific community as a whole and to move towards that end, new developements, tools and techniques are needed. Nowadays, many small research groups are capable of producing important and interesting datasets. The release of those datasets can greatly increase their scientific value. In addition, the development of new data analysis algorithms greatly benefits from the availability of a big corpus of annotated datasets for training and testing purposes, giving new and better algorithms to biomedical sciences in return. None of these would be feasible without large amounts of biological data made freely and publicly available. Dissemination The Distributed Annotation System (DAS) is a protocol designed to publish and integrate annotations on biological entities in a distributed way. DAS is structured as a client-server system where the client retrieves data from one or more servers and to further process and visualise. Nowadays, setting up a DAS server imposes some requirements not met by many research groups. With the aim of removing the hassle of setting up a DAS server, a new software platform has been developed: easyDAS. easyDAS is a hosted platform to automatically create DAS servers. Using a simple web interface the user can upload a data file, describe its contents and a new DAS server will be automatically created and data will be publicly available to DAS clients. Visualisation One of the most broadly used visualization paradigms for genomic data are genomic browsers. A genomic browser is capable of displaying different sets of features positioned relative to a sequence. It is possible to explore the sequence and the features by moving around and zooming in and out. When this project was started, in 2007, all major genome browsers offered quite an static experience. It was possible to browse and explore data, but is was done through a set of buttons to the genome a certain amount of bases to left or right or zooming in and out. From an architectural point of view, all web-based genome browsers were very similar: they all had a relatively thin clien-side part in charge of showing images and big backend servers taking care of everything else. Every change in the display parameters made by the user triggered a request to the server, impacting the perceived responsiveness. We created a new prototype genome browser called GenExp, an interactive web-based browser with canvas based client side data rendering. It offers fluid direct interaction with the genome representation and it's possible to use the mouse drag it and use the mouse wheel to change the zoom level. GenExp offers also some quite unique features, such as its multi-window capabilities that allow a user to create an arbitrary number of independent or linked genome windows and its ability to save and share browsing sessions. GenExp is a DAS client and all data is retrieved from DAS sources. It is possible to add any available DAS data source including all data in Ensembl, UCSC and even the custom ones created with easyDAS. In addition, we developed a javascript DAS client library, jsDAS. jsDAS is a complete DAS client library that will take care of everything DAS related in a javascript application. jsDAS is javascript library agnostic and can be used to add DAS capabilities to any web application. All software developed in this thesis is freely available under an open source license.<br>Les recents millores tecnològiques han portat a una explosió en la quantitat de dades biològiques que es generen i a l'aparició de nous reptes en el camp de la gestió de les dades biològiques. Per a maximitzar el coneixement que podem extreure d'aquestes ingents quantitats de dades cal que solucionem el problemes associats al seu anàlisis, i en particular a la seva disseminació i visualització. La compartició d'aquestes dades de manera lliure i gratuïta pot beneficiar en gran mesura a la comunitat científica i a la societat en general, però per a fer-ho calen noves eines i tècniques. Actualment, molts grups són capaços de generar grans conjunts de dades i la seva publicació en pot incrementar molt el valor científic. A més, la disponibilitat de grans conjunts de dades és necessària per al desenvolupament de nous algorismes d'anàlisis. És important, doncs, que les dades biològiques que es generen siguin accessibles de manera senzilla, estandaritzada i lliure. Disseminació El Sistema d'Anotació Distribuïda (DAS) és un protocol dissenyat per a la publicació i integració d'anotacions sobre entitats biològiques de manera distribuïda. DAS segueix una esquema de client-servidor, on el client obté dades d'un o més servidors per a combinar-les, processar-les o visualitzar-les. Avui dia, però, crear un servidor DAS necessita uns coneixements i infraestructures que van més enllà dels recursos de molts grups de recerca. Per això, hem creat easyDAS, una plataforma per a la creació automàtica de servidors DAS. Amb easyDAS un usuari pot crear un servidor DAS a través d'una senzilla interfície web i amb només alguns clics. Visualització Els navegadors genomics són un dels paradigmes de de visualització de dades genòmiques més usats i permet veure conjunts de dades posicionades al llarg d'una seqüència. Movent-se al llarg d'aquesta seqüència és possibles explorar aquestes dades. Quan aquest projecte va començar, l'any 2007, tots els grans navegadors genomics oferien una interactivitat limitada basada en l'ús de botons. Des d'un punt de vista d'arquitectura tots els navegadors basats en web eren molt semblants: un client senzill encarregat d'ensenyar les imatges i un servidor complex encarregat d'obtenir les dades, processar-les i generar les imatges. Així, cada canvi en els paràmetres de visualització requeria una nova petició al servidor, impactant molt negativament en la velocitat de resposta percebuda. Vam crear un prototip de navegador genòmic anomenat GenExp. És un navegador interactiu basat en web que fa servir canvas per a dibuixar en client i que ofereix la possibilitatd e manipulació directa de la respresentació del genoma. GenExp té a més algunes característiques úniques com la possibilitat de crear multiples finestres de visualització o la possibilitat de guardar i compartir sessions de navegació. A més, com que és un client DAS pot integrar les dades de qualsevol servidor DAS com els d'Ensembl, UCSC o fins i tot aquells creats amb easyDAS. A més, hem desenvolupat jsDAS, la primera llibreria de client DAS completa escrita en javascript. jsDAS es pot integrar en qualsevol aplicació DAS per a dotar-la de la possibilitat d'accedir a dades de servidors DAS. Tot el programari desenvolupat en el marc d'aquesta tesis està lliurement disponible i sota una llicència de codi lliure.

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Simpson, T. "Visualisation of irregular, finite element data." Thesis, Swansea University, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.639040.

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This thesis outlines work into the development of efficient techniques for visualisation of datasets generated using finite element analyses. In particular, the work concentrates on datasets that require quadratic interpolation methods to accurately visualise simulation results. Typically for example, this includes simulations into non-Newtonian fluids where the use of quadratic shape functions is necessary to obtain acceptable results. Our first concern is fundamental algorithms for analysing irregular domains, typically constructed from triangular or tetrahedral cells. This includes methods for reducing the search space through domain space decomposition (octrees) and point location tests for interpolation. To this end, a new octree method is introduced, termed the “extended-nodes” octree which is shown to be a space-efficient data structure for irregular grids. The work continues to describe how commonly used visualisation techniques such as surface tiling and volume rendering can be adapted to work with quadratic interpolation functions over irregular grids. Particular interest is given to image quality and algorithm efficiency. In the context of volume rendering, a staged interpolation function is described based on a standard method found in the literature. This is shown to be substantially quicker whilst giving visually identical results. For surface tiling, a new recursive, adaptive algorithm is described which solves many of the problems encountered when tiling higher-order surfaces. The work on surface visualisation culminates in the introduction of a new algorithm termed Irregular, Quadratic, Direct Surface Rendering (IQDSR). This ray-casting method is shown to produce high-quality images of quadratic iso-surfaces within finite element data in a highly efficient manner. Finally, consideration is given to the visualisation of fluid flow (vector) data, common within finite element analysis. In particular, a review of both volume rendering based methods is given, along with a more in-depth discussion into particle based methodologies. Altogether, this work gives both a review of current linear finite element scalar and vector visualisation algorithms, and outlines new techniques which extend these methods to utilise quadratic interpolation functions over irregular meshes.

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Turner, D. "The visualisation of polarimetric radar data." Thesis, University of Edinburgh, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.663102.

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This research forms part of a larger body of work which studies the application of scientific visualisation to the analysis of large multi-valued datasets. Visualisation techniques have historically assumed a fundamental role in the analysis of patterns in geographic datasets. This is particularly apparent in the analysis of remotely sensed data, which, since the advent of aerial photography, has utilised the intensity of visible (and invisible) electromagnetic energy as a means of producing synoptic map-like images. Progress in remote sensing technology, however, has led to the development of systems which measure very large numbers of intensity ‘channels’, or require the analysis of variables other than intensity values. Current visualisation strategies are insufficient to adequately represent such datasets, whilst retaining the synoptic perspective. In response to this, two new visualisation techniques are presented for the analysis of polarimetric radar data. Both techniques demonstrate how it is possible to produce synoptic image suitable for the analysis of spatial patterns without relying on pixel-based intensity images. This allows a large number of variables to be ascribed to a single geographic location, and thus encourages the rapid identification of patterns and anomalies within datasets. The value of applying the principals of scientific visualisation to exploratory data analysis is subsequently demonstrated with reference to a number of case studies that highlight the potential of the newly developed techniques.

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Loizides, Andreas M. "Intuitive visualisation of multi-variate data sets using the empathic visualisation algorithm (EVA)." Thesis, University College London (University of London), 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.407941.

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Książki na temat "Data Visualisation"

Rahlf, Thomas. Data Visualisation with R. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-28444-2.

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Rahlf, Thomas. Data Visualisation with R. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-49751-8.

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Shah, Neel. Visualisation of electricity market data. Manchester: University of Manchester, Department of Computer Science, 1996.

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Hall, Tim. 3D visualisation of mobile robot sensr data. Manchester: University of Manchester, Department of Computer Science, 1997.

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Bianconi, Francesco. Data and Process Visualisation for Graphic Communication. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-57051-3.

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Pryke, Andy Neil. Data mining using genetic algorithms and interactive visualisation. Birmingham: University of Birmingham, 1999.

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Ruddy, David Andrew. Sharing of data visualisation within a virtual organisation. Oxford: Oxford Brookes University, 2003.

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Ottoson, Patrik. Geographic indexing and data management for 3D-visualisation. Stockholm: Royal Institute of Technology, KTH, 2001.

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Hobbs, Kenneth Frank. The visualisation and rendering of digital elevation data. London: University of East London, 2000.

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Foreman, Darren. Visualisation of data structures and operations on them. Manchester: University of Manchester, 1995.

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Części książek na temat "Data Visualisation"

Fox, Charles. "Data Visualisation." In Springer Textbooks in Earth Sciences, Geography and Environment, 125–45. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-72953-4_9.

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Gough, Phillip, and Jack Zhao. "Data Visualisation." In Teaching Science Students to Communicate: A Practical Guide, 57–68. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-030-91628-2_7.

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Shardt, Yuri A. W. "Data Visualisation." In essentials, 9–22. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-40299-9_2.

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Irwin, Terry, Julie Terberg, and Echo Swinford. "Data visualisation." In Medical Presentations, 151–66. Boca Raton: CRC Press, 2024. http://dx.doi.org/10.1201/9781003287902-19.

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Dawson, Catherine. "Data visualisation." In A–Z of Digital Research Methods, 86–92. Abingdon, Oxon ; New York, NY : Routledge, 2019.: Routledge, 2019. http://dx.doi.org/10.4324/9781351044677-14.

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Aitkin, Murray. "Data visualisation." In Introduction to Statistical Modelling and Inference, 111–16. Boca Raton: Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003216025-9.

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Shardt, Yuri A. W. "Data Visualisation." In Using Excel to Solve Statistical Problems: A Practical Guide to the Book “Statistics for Chemical and Process Engineers”, 15–33. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-65449-7_2.

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Kjeldsen, Thomas Rodding. "Data Visualisation." In Risk and Uncertainty for Civil Engineering, 52–64. London: CRC Press, 2025. https://doi.org/10.1201/9781032700373-4.

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Frampton, Michael. "Visualisation." In Complete Guide to Open Source Big Data Stack, 295–337. Berkeley, CA: Apress, 2018. http://dx.doi.org/10.1007/978-1-4842-2149-5_9.

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Moore, Antoni, Marcos de Oliveira, Carlos Caminha, Vasco Furtado, Victor Basso, and Leonardo Ayres. "Applying Geovisual Analytics to Volunteered Crime Data." In Geospatial Visualisation, 185–209. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-12289-7_9.

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Streszczenia konferencji na temat "Data Visualisation"

Lourenço, Luis, Paulo Figueiras, Amin Khodamoradi, André Grilo, Bruno Rêga, Ruben Costa, and Ricardo Jardim-Goncalves. "Big Data Visualisation in the Maritime Industry." In 2024 IEEE International Conference on Engineering, Technology, and Innovation (ICE/ITMC), 1–8. IEEE, 2024. https://doi.org/10.1109/ice/itmc61926.2024.10794236.

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Matsuno, Ryuta, Keita Sakuma, and Masakazu Hirokawa. "Model Accuracy-Oriented Data Sets Visualization for Understanding Temporal Changes in Data." In 2024 28th International Conference Information Visualisation (IV), 186–89. IEEE, 2024. http://dx.doi.org/10.1109/iv64223.2024.00041.

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Villuendas, Esperanza, Laya Targa, Álvaro Solbes, Inmaculada Coma, Jorge Sebastián, and Cristina Portalés. "USABILITY EVALUATION FOR DATA VISUALISATION OF CULTURAL HERITAGE." In 19th International Technology, Education and Development Conference, 2975–84. IATED, 2025. https://doi.org/10.21125/inted.2025.0786.

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Cotta, Romulo, and Robert Cottis. "Methods for the Visualisation of Electrochemical Noise Data." In CORROSION 2007, 1–10. NACE International, 2007. https://doi.org/10.5006/c2007-07363.

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Abstract The use of electrochemical noise (EN) measurements for the study of corrosion processes is now well established, but it remains somewhat unclear as to the best methods to use the extract useful information from the measured time records. Many of the simpler methods are based on the calculation of statistical parameters, such as the standard deviation of current, σI, or potential, σE, and the electrochemical noise resistance, Rn. A problem with many parameters derived from EN measurements is they are inherently noisy, which can make interpretation difficult. This paper explores an alternative method of plotting these parameters that may offer some advantages. The method is inspired by the method developed by Schmitt, and the relationship between this method and conventional statistical parameters is examined.

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Cunha Monteiro, Walbert, Thiago Augusto Soares de Sousa, Anderson Gregório Marques Soares, Tiago Davi Oliveira de Araújo, Carlos Gustavo Resque dos Santos, and Bianchi Serique Meiguins. "Encoding Data Through Tactile Vibrations." In 2024 28th International Conference Information Visualisation (IV), 1–6. IEEE, 2024. http://dx.doi.org/10.1109/iv64223.2024.00011.

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Williams, Alice, and Boris Kovalerchuk. "Synthetic Data Generation and Automated Multidimensional Data Labeling for AI/ML in General and Circular Coordinates." In 2024 28th International Conference Information Visualisation (IV), 272–79. IEEE, 2024. http://dx.doi.org/10.1109/iv64223.2024.00054.

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Oliveira, Beatriz, and Jorge Sá. "Data Feminism Influence on Data Visualization." In 23ª Conferência da Associação Portuguesa de Sistemas de Informação. Associação Portuguesa de Sistemas de Informação, APSI, 2023. http://dx.doi.org/10.18803/capsi.v23.365-381.

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Data Visualisation is currently seen as a powerful communication tool, as the human mind is more receptive to visual information than words or raw data. However, most existing visualisations are done from an androcentric perspective. This article proposes Data Visualisation from a feminist perspective. To this end, concepts such as Feminism, Data Visualisation and Data Feminism will be addressed to arrive at the concept of Data Visualisation in Feminism, resulting in a set of guidelines and recommendations to be incorporated when designing Data Visualisations. As part of the work carried out, an existing data visualisation was selected and analysed, highlighting the guidelines of Data Feminism in Data Visualisation. As a result, a recreation of this visualisation is proposed, incorporating the Data Feminism guidelines. It was found that the resulting visualisation is different from the original and is aligned with the concepts of Data Feminism.

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Pinney, Joel, Fiona Carroll, and Esyin Chew. "Enthusiast Versus Antagonist: Exploring the Perceptions of Data Experts on the Visualisation of Uncertainty." In Human Interaction and Emerging Technologies (IHIET-AI 2022) Artificial Intelligence and Future Applications. AHFE International, 2022. http://dx.doi.org/10.54941/ahfe100892.

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Despite the copious number of reasons to visualise uncertainty in visualisations, there is still a reluctance to actively represent uncertainties. This paper explores the perceptions of data experts considering uncertainty visualisation and their reasoning behind lacking engagement. By documenting a series of interviews with data experts, the authors uncover the perceptions and constraints faced when contemplating uncertainty visualisation. Through several industries, the authors reveal numerous perceived benefits of uncertainty visualisation but also the strong influence end-users have on the decision to incorporate the additional information. Finally, the paper reflects on a lack of experience but also the commitment from the data experts to the use of aesthetics in developing intuitive uncertainty visualisations. Whilst also highlighting their perceived benefits around what the aesthetic could bring to both visualisation development and uncertainty visualisation design. The study documented in this paper feeds into a larger body of research on aesthetic uncertainty visualisation.

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Monageng, Keabetswe, Annlizé L. Marnewick, and Carl Marnewick. "Visualisation of Project Data for Informed Decision-Making." In The 33rd IPMA World Congress “Hope for a Sustainable Future: Blending AI&IT, ESG, and Capital Projects”, 1–19. International Project Management Association – IPMA, International Project Management Association - South Africa NPC (IPMA-SA), 2025. https://doi.org/10.56889/mimn3363.

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Data creates opportunities for project managers to visualise the data which is valuable in project management decision-making. Without a thorough view of the data, project managers are unable to make informed decisions. Data visualisation presents data in pictures or graphs that summarise the information in a comprehensible manner with the purpose of gaining insights and drawing conclusions. A questionnaire consisting of four sections was completed by 39 respondents. One section focused on the usage and influences of data visualisations. Another section focused on specific data visualisation techniques. The results indicate that the most popular visualisation techniques are bar and line charts, with violin plots the least used. Five different charts are used to eliminate bias and to develop future strategies. Gauges, radar charts and tables are not perceived as visualisation techniques that can be used for decision-making. From a theoretical standpoint, certain visualisation techniques hold more prominence and utility than others. Bar and line charts are evidently favoured due to their simplicity and effectiveness in conveying data. Conversely, violin plots seem underutilised, indicating potential gaps in understanding or reluctance to explore more advanced methods. Project managers should prioritise the use of bar and line charts for data representation, ensuring clarity and accessibility in communication.

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Ivancic, M., Z. Mihajlovic, and I. Ivancic. "Seismic data visualisation." In 2015 38th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO). IEEE, 2015. http://dx.doi.org/10.1109/mipro.2015.7160287.

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Raporty organizacyjne na temat "Data Visualisation"

Caldwell, T. G., and H. M. Bibby. Visualisation of Tensor Time Domain Electromagnetic Data. Office of Scientific and Technical Information (OSTI), January 1995. http://dx.doi.org/10.2172/895937.

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Valero Sancho, JL, J. Catalá Domínguez, and BE Marín Ochoa. An approach to the taxonomy of data visualisation. Revista Latina de Comunicación Social, July 2014. http://dx.doi.org/10.4185/rlcs-2014-1021en.

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Marín Ochoa, BE. Treatment of post-conflict Colombia through infographics and data visualisation. Revista Latina de Comunicación Social, April 2018. http://dx.doi.org/10.4185/rlcs-2018-1277en.

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Kirkby, A. L., F. Zhang, J. Peacock, R. Hassan, and J. Duan. Development of the open-source MTPy package for magnetotelluric data analysis and visualisation. Geoscience Australia, 2020. http://dx.doi.org/10.11636/132198.

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Zhan, Peng. Statistical Analysis and Data Visualization in R. Instats Inc., 2022. http://dx.doi.org/10.61700/dizyg5iq1mqj5469.

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This seminar provides a gentle introduction to R for those looking to use it for applied statistics and visualisation, covering a range of essential topics on basic data manipulation, regression analysis, and visualizing data and results. Examples from multiple fields are used to demonstrate the applications. An official Instats certificate of completion is provided at the conclusion of the seminar.

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Pălici, Bogdan, Alin Savu, Maria Trifon, Cristian Georgescu, Cătălin Toma, Alexandru Mihăilescu, and Gabriel Simion. Mapping - Interactive Tool for Exploring Statistical Data about Cultural Infrastructure in Romania. National Institute for Cultural Research and Training, 2021. http://dx.doi.org/10.61789/mod.cdi.crtg.en.21.

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The Cartographic Module is an instrument for data selection, structuring, visualisation and analysis. It provides for multiple selection functionalities both at geographical area level (county, locality) and at data level (category of indicators and indicators). Three types of dynamic graphs are available on the indicator pages: comparison/evolution, ranking and frequency.

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Gruber, Peter. Using ChatGPT for Advanced Data Analysis. Instats Inc., 2023. http://dx.doi.org/10.61700/pmgm4wmm7ffer469.

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This workshop teaches researchers, from PhD students to professors, how to use ChatGPT and its Advanced Data Analytics tool for statistical analysis without writing a line of code or even knowing how to use a statistics program. The seminar covers a range of topics from data preparation and descriptive statistics to regression analysis, advanced statistical tests and visualisation. Special emphasis is placed on understanding the workings and limits of AI models such as ChatGPT and reflecting on its implications for data analysis.

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Toutin, Th, A. Redmond, E. Hoeppner, D. Hoja, and C. King. RADARSAT and DEM Data Fusion for 3D Visualisation Over the Reunion Island for Geoscientific Applications. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1998. http://dx.doi.org/10.4095/219317.

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Gruber, Peter H. Using ChatGPT for Advanced Data Analysis. Instats Inc., 2023. http://dx.doi.org/10.61700/zqir2dzchct5b469.

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This 2-day workshop teaches researchers, from PhD students to professors, how to use ChatGPT and its Advanced Data Analytics tool for statistical analysis without writing a line of code or even knowing how to use a statistics program. The seminar covers a range of topics from data preparation and descriptive statistics to regression analysis, advanced statistical tests and visualisation. Special emphasis is placed on understanding the workings and limits of AI models such as ChatGPT and reflecting on its implications for data analysis.

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VijilMorin, Alejandra, Yomna El-Serafy, Taskeen Adam, and Björn Haßler. Data collection and visualisation tools in the education sector in sub-Saharan Africa and South Asia. EdTech Hub, August 2022. http://dx.doi.org/10.53832/edtechhub.0151.

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